首页|Researchers from University of Nottingham Report Recent Findings in Artificial Intelligence (A Modular Artificial Intelligence and Asset Administration Shell Approach To Streamline Testing Processes In Manufacturing Services)
Researchers from University of Nottingham Report Recent Findings in Artificial Intelligence (A Modular Artificial Intelligence and Asset Administration Shell Approach To Streamline Testing Processes In Manufacturing Services)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Elsevier
Fresh data on Artificial Intelligence are presented in a new report. According to news originating from Nottingham, United Kingdom, by NewsRx correspondents, research stated, “The increasing demand for personalized products and cost-effectiveness has highlighted the necessity of integrating intelligence into production systems. This integration is crucial for enabling intelligent control that can adapt to variations in features, parts, and conditions, thereby enhancing functionalities while reducing costs.” Financial support for this research came from DiManD Innovative Training Network (ITN) project European Union through the Marie Sklodowska-Curie Innovative Training Networks (H2020-MSCAITN2018). Our news journalists obtained a quote from the research from the University of Nottingham, “This research emphasizes the incorporation of intelligence in testing processes within production systems. We introduce a novel approach for controlling testing functionality using an asset administration shell enriched with modular artificial intelligence. The proposed architecture is not only effective in controlling the execution behavior through services but also offers the distinct advantage of a modular design. This modularity significantly contributes to the system’s adaptability and scalability, allowing for more efficient and cost-effective solutions as different machine-learning models may be substituted to meet requirements.” According to the news editors, the research concluded: “The effectiveness of this approach is validated through a practical use case of leak testing, demonstrating the benefits of the modular architecture in a real-world application.” This research has been peer-reviewed.
NottinghamUnited KingdomEuropeArtificial IntelligenceEmerging TechnologiesMachine LearningUniversity of Nottingham
NETL
NSTL
Elsevier
